Tag Archives: Data collection

Let’s say you want to find out how well students’ think they learned theory in your class.

One option is to do a pre/post test: You distribute the same survey before and after the class asking them to rate on 1-4 scale how well they think they know the new material. Then you compare their ratings.

Another option is to do posttest only: You could give them a survey after the class that asks them to rate 1-4 their knowledge before the class and 1-4 their knowledge now. Then you compare their ratings.

One research option is stronger than the other. Which one is it? and Why? (hint: think retrospective/prospective)

Like this:

Actually when it comes to quantitative data, there are 4 levels, but who’s counting? (Besides Goldilocks.)

Nominal (categorical) data are names or categories: (gender, religious affiliation, days of the week, yes or no, and so on)

Ordinal data are like the pain scale. Each number is higher (or lower) than the next but the distances between numbers are not equal. In others words 4 is not necessarily twice as much as 2; and 5 is not half of 10.

Interval data are like degrees on a thermometer. Equal distance between them, but no actual “0”. 0 degrees is just really, really cold.

In honor of Nurse Week, I offer this tribute to the avante garde research work of Florence Nightingale in the Crimea that saved lives and set a precedent worth following.

Nightingale was a “passionate statistician” knowing that outcome data are convincing when one wants to change the world. She did not merely collect the data, but also documented it in a way that revealed its critical meaning for care.

As noted by John H. Lienhard (1998-2002): “Once you see Nightingale’s graph, the terrible picture is clear. The Russians were a minor enemy. The real enemies were cholera, typhus, and dysentery. Once the military looked at that eloquent graph, the modern army hospital system was inevitable. You and I are shown graphs every day. Some are honest; many are misleading….So you and I could use a Florence Nightingale today, as we drown in more undifferentiated data than anyone could’ve imagined during the Crimean War.” (Source: Leinhard, 1998-2002)

As McDonald (2001) writes in the BMJ free, full-text, Nightingale was “a systemic thinker and a “passionate statistician.” She insisted on improving care by making policy & care decisions based on “the best available government statistics and expertise, and the collection of new material where the existing stock was inadequate.”(p.68)

Moreover, her display of the data brought its message home through visual clarity!

Thus while Nightingale adhered to some well-accepted, but mistaken, scientific theories of the time (e.g., miasma) her work was superb and scientific in the best sense of the word. We could all learn from Florence.

CRITICAL THINKING: What issue in your own practice could be solved by more data? How could you collect that data? If you have data already, how can you display it so that it it meaningful to others and “brings the point home”?